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SOD1 Mutations Targeting Surface Hydrogen Bonds Promote Amyotrophic Lateral Sclerosis without Reducing Apo-state Stability*

Open AccessPublished:February 26, 2010DOI:https://doi.org/10.1074/jbc.M109.086074
      In good accord with the protein aggregation hypothesis for neurodegenerative diseases, ALS-associated SOD1 mutations are found to reduce structural stability or net repulsive charge. Moreover there are weak indications that the ALS disease progression rate is correlated with the degree of mutational impact on the apoSOD1 structure. A bottleneck for obtaining more conclusive information about these structure-disease relationships, however, is the large intrinsic variability in patient survival times and insufficient disease statistics for the majority of ALS-provoking mutations. As an alternative test of the structure-disease relationship we focus here on the SOD1 mutations that appear to be outliers in the data set. The results identify several ALS-provoking mutations whose only effect on apoSOD1 is the elimination or introduction of a single charge, i.e. D76V/Y, D101N, and N139D/K. The thermodynamic stability and folding behavior of these mutants are indistinguishable from the wild-type control. Moreover, D101N is an outlier in the plot of stability loss versus patient survival time by having rapid disease progression. Common to the identified mutations is that they truncate conserved salt-links and/or H-bond networks in the functional loops IV or VII. The results show that the local impact of ALS-associated mutations on the SOD1 molecule can sometimes overrun their global effects on apo-state stability and net repulsive charge, and point at the analysis of property outliers as an efficient strategy for mapping out new ALS-provoking features.

      Introduction

      As in other soluble proteins, the charged and polar side chains of SOD1 are found in connection to the protein surface where they protrude freely into the solvent or are involved in solvent-accessible salt links and hydrogen bonds (Fig. 1). Replacement of such surface groups by point mutation has typically small effects on protein folding and stability. Even so, charged side chains have been observed to play key roles in controlling protein-protein interactions and aggregation. This control can either be exerted in the context of the folded structure by, e.g. providing edge protection of β-sheets (
      • Otzen D.E.
      • Kristensen O.
      • Oliveberg M.
      ,
      • Richardson J.S.
      • Richardson D.C.
      ), or by modulation the aggregation propensity of the unfolded chain (
      • Otzen D.E.
      • Kristensen O.
      • Oliveberg M.
      ,
      • Chiti F.
      • Stefani M.
      • Taddei N.
      • Ramponi G.
      • Dobson C.M.
      ). In this perspective it is interesting that 48 out of the 142 SOD1 mutations that have so far been linked to the neurodegenerative disease amyotrophic lateral sclerosis (ALS)
      The abbreviations used are: ALS
      amyotrophic lateral sclerosis
      MES
      4-morpholineethanesulfonic acid
      PDB
      Protein Data Bank.
      involve charge replacements (
      Alsod
      ) (supplemental Table S1). Like most proteins, SOD1 carries a net negative charge under physiological conditions, which assure some degree of electrostatic repulsion between the molecular components in the crowded cellular interior. Strikingly, 83% of the ALS-mutations targeting SOD1 charges are found to decrease this net repulsive charge (
      • Sandelin E.
      • Nordlund A.
      • Andersen P.M.
      • Marklund S.S.
      • Oliveberg M.
      ) and genetic data suggest the loss of a single negative charge is enough to trigger ALS (
      • Sandelin E.
      • Nordlund A.
      • Andersen P.M.
      • Marklund S.S.
      • Oliveberg M.
      ). At the other end of the spectrum are the ALS-associated mutations of hydrophobic residues in the SOD1 interior and of the loop glycines (Fig. 1). The common effect of these mutations is to destabilise the SOD1 framework by shifting the folding equilibrium toward the denatured state. For some mutants, e.g. A4V and G93A, the protein is even destabilised to the extent that the nascent chain cannot fold under physiological conditions without oxidation of the Cys57–Cys146 disulfide bridge or acquisition of the native metals (
      • Lindberg M.J.
      • Normark J.
      • Holmgren A.
      • Oliveberg M.
      ). Taken together, this tendency of the ALS-associated SOD1 mutations to reduce either repulsive charge or structural stability point at protein aggregation as a deterministic factor in ALS (
      • Sandelin E.
      • Nordlund A.
      • Andersen P.M.
      • Marklund S.S.
      • Oliveberg M.
      ,
      • Shaw B.F.
      • Valentine J.S.
      ). This physical-chemical link to protein aggregation complies also with the occurrence of pathological SOD1 inclusions in the spinal cord of ALS patients (
      • Shibata N.
      • Hirano A.
      • Kobayashi M.
      • Sasaki S.
      • Kato T.
      • Matsumoto S.
      • Shiozawa Z.
      • Komori T.
      • Ikemoto A.
      • Umahara T.
      ,
      • Shibata N.
      • Hirano A.
      • Kobayashi M.
      • Asayama K.
      • Umahara T.
      • Komori T.
      • Ikemoto A.
      ,
      • Watanabe M.
      • Dykes-Hoberg M.
      • Culotta V.C.
      • Price D.L.
      • Wong P.C.
      • Rothstein J.D.
      ,
      • Jonsson P.A.
      • Ernhill K.
      • Andersen P.M.
      • Bergemalm D.
      • Brännström T.
      • Gredal O.
      • Nilsson P.
      • Marklund S.L.
      ). Another conspicuous feature of the ALS mechanism is that several of the SOD1 mutations show a characteristic uniform disease progression. For example, the survival time after symptomatic onset for patients carrying the A4V is invariable short (<2 years), whereas the survival time for patients with the H46R is always very long (≫10 years). On this basis several investigations have been directed to examine if there is a coupling between the physical-chemical properties of the ALS-provoking SOD1 mutations and the severity of disease (
      • Lindberg M.J.
      • Tibell L.
      • Oliveberg M.
      ,
      • Wang Q.
      • Johnson J.L.
      • Agar N.Y.
      • Agar J.N.
      ,
      • Andersen P.M.
      ). That is, are the most perturbing mutations also the ones that cause the worse damage? Regarding the age of onset there is no apparent trend, most mutations for which reliable data are available has a mean age of onset of 46–47 years (
      • Andersen P.M.
      ), indicating the ALS mechanism in this respect is different from that of Lund-Huntington disease where the length of the poly(Q) additions correlates with age of onset of clinical symptoms (
      • Chen S.M.
      • Ferrone F.A.
      • Wetzel R.
      ,
      • Landles C.
      • Bates G.P.
      ). When it comes to the disease progression, however, the thermodynamic stability of the apoSOD1 species hints at a weak correlation with survival time after first diagnosis for a subset of non-charged ALS mutations selected on the basis of good clinical statistics (
      • Lindberg M.J.
      • Bystrom R.
      • Boknas N.
      • Andersen P.M.
      • Oliveberg M.
      ). This trend has also been discerned with a more extensive set of ALS mutations even though the scatter of the data is close to abbreviate the significance of the signal (
      • Wang Q.
      • Johnson J.L.
      • Agar N.Y.
      • Agar J.N.
      ). The main problem is uncertain survival statistics because of low patient numbers. For the majority (76%) of the ALS-associated SOD1 mutations there are less than 5 reported disease cases and this shortage of data is particularly alarming for mutations with long survival times (supplemental Table S1). In addition to this statistical uncertainty, however, there seems also to be mutations that simply break the pattern. A good example of such a statistically safe outlier is the mutation D101N. This mutation yields a thermal melting transition close to that of the wild-type protein and is still associated with patient survival times of <5 years (n = 17). In sharp contrast, the more destabilizing ALS mutation D90A displays typically survival times >5 years (n = 15) despite having the same effect on the net repulsive charge. Both mutations reduce the charge of the apoSOD1 monomer from −6 to −5 accordingly, it is reasonable to assume that these differences in survival time stem from specific effects on the SOD1 molecule or its interaction with cellular components that go beyond any underlying dependence on the global parameters net charge and thermodynamic stability. In this study, we have systematically tried to verify and extend the set of property outliers to see if these deviating SOD1 mutations can reveal new clues to the ALS mechanism. The analysis identifies 5 ALS-associated charge mutations with apo-state stabilities and global folding transitions identical to those of the wild-type protein, i.e. D76V, D76Y, D101N, N139D, and N139K. The results provide direct experimental support for the genetic indication that reduction of the net charge by just one unit induces ALS with high penetrance. Moreover, the data point at an additional molecular factor in the mechanism of SOD-induced ALS: the rupture of conserved hydrogen-bond networks at the SOD1 surface.
      Figure thumbnail gr1
      FIGURE 1The distribution of charged, polar, and hydrophobic amino acids in the SOD1 structure (PDB entry 1HL5) is shown as sticks. Positions with ALS-associated mutations are marked as spheres in the right monomer only. A, SOD1 dimer showing the positions of charged side chains, D (blue), E (light blue), K (red), and R (bright red), and histidines (cyan). B, structural positions of the polar (beige) side chains (S, T, C, N, and Q). C, structural positions of the hydrophobic (green) side chains (A, V, F, M, I, W, and L). Proline (white) and glycine (yellow). D, SOD1 amino acid sequence indicating the degree of side chain conservation across 17 eukaryotic species as visualized by Homologene (). The degree of conservation is measured in bits (log2(20) = 4.3 bits, where 20 is the number of possible amino acids in a peptide chain). For each sequence position there is a stack of amino acid occurrences. The height of each stack indicates the sequence conservation for that position (
      • Crooks G.E.
      • Hon G.
      • Chandonia J.M.
      • Brenner S.E.
      ). The height of each letter reflects the relative frequency for the amino acid in question and the letter at the top of each stack is the most frequent in that position. Multiple alignments were made with the T-coffee software using default parameters (
      • Notredame C.
      • Higgins D.G.
      • Heringa J.
      ). The consensus sequence was made with the WebLogo software (
      • Crooks G.E.
      • Hon G.
      • Chandonia J.M.
      • Brenner S.E.
      ).

      EXPERIMENTAL PROCEDURES

      All experiments were done on apo-protein under oxidizing conditions with the intramolecular disulfide bridge between Cys57 and Cys146 kept intact.

      Protein Preparation

      All mutants were made on a background of C6A/C111A and for the monomers on C6A/C111A/F50E/G51E. The proteins were coexpressed with the copper chaperone (yCCS) as described in Ref.
      • Lindberg M.J.
      • Tibell L.
      • Oliveberg M.
      . The apo-protein was prepared as described in Ref.
      • Lindberg M.J.
      • Normark J.
      • Holmgren A.
      • Oliveberg M.
      . The standard buffer was 10 mm MES (pH 6.3) with 10 mm EDTA to maintain the proteins as metal-free.

      Kinetic Measurements

      Stopped-flow measurements were performed on a SX-17MV stopped-flow spectrofluorometer (Applied Photophysics, Leatherhead, UK) with excitation at 280 nm and emission detection above 320 nm using a cut-off filter. For slow relaxations, i.e. k < 0.003 s−1, additional measurements were done by manual mixing with detection on a FP-6500 spectrofluorometer (Jasco). All measurements were done at 25 °C and at a final SOD1 concentration of 4 μm monomer. Urea was used as denaturant (ultra PURE; MP Biomedicals, Solon, OH).

      Data Analysis

      Under the assumption of two-state kinetics for the apoSOD1 monomer (
      • Lindberg M.J.
      • Normark J.
      • Holmgren A.
      • Oliveberg M.
      ), protein stability was derived from chevron data according to Equation 1,
      ΔGDM=RTInKDM=RTln(kuH2O/kfH2O)
      (Eq. 1)


      where ΔGD–M is the protein stability, KD–M = [D]/[M], ku is the unfolding rate constant, and kf is the unfolding rate constant. The plots of log kf and log ku versus [urea] were fitted by Refs.
      • Lindberg M.J.
      • Normark J.
      • Holmgren A.
      • Oliveberg M.
      and
      • Fersht A.
      ) in Equation 2,
      logkobs=log(kf+ku)=log(10logkfH2O+m f[urea]+10logkuH2O+m u[urea])
      (Eq. 2)


      where kfH2O and kuH2O are the rate constants at [urea] = 0 m, and mf and mu are the slopes of the refolding and unfolding limbs, respectively. The stability changes caused by point mutations were calculated from Equation 3,
      ΔΔGDMmut=ΔGDMpWTΔGDMmut=2.3RT(ΔlogkfH2OΔlogkuH2O)
      (Eq. 3)


      where ΔGD–MpWT is the stability of the pseudo-WT and ΔGD–Mmut is the stability of the mutant protein. ΔlogkfH2O and ΔlogkuH2O are the mutant-induced changes of the rate constants. The changes in stability upon mutation of dimeric apoSOD was calculated from
      • Lindberg M.J.
      • Normark J.
      • Holmgren A.
      • Oliveberg M.
      in Equation 4,
      ΔΔG2DMmut =ΔΔGDMmut +(2.3RT(logkdpWTlogkdmut ))
      (Eq. 4)


      where logkd is the dimer dissociation rate constant at 5.8 m [urea]. For data analysis, we used KALEIDAGRAPH software (Synergy Software, Reading, PA).

      Normalization of Protein Stabilities

      To be able to compare mutant stabilities measured by denaturant-induced and thermal unfolding we normalized the data as follows. For denaturant-induced measurements, the normalized destabilization upon point mutation (ΔΔGnorm) was estimated as Equation 5,
      ΔΔGnorm =1(ΔΔGobs ΔΔGMIN )/(ΔΔGMAX ΔΔGMIN ),
      (Eq. 5)


      where ΔΔGobs is the observed destabilization for the mutation in question, and ΔΔGMAX and ΔΔGMIN are the maximum and minimum values of the dataset taken from Table 2 in Ref.
      • Lindberg M.J.
      • Bystrom R.
      • Boknas N.
      • Andersen P.M.
      • Oliveberg M.
      . For the thermal data, ΔΔGnorm was correspondingly derived as Equation 6,
      ΔΔGnorm =1(ΔTmobs ΔTmMIN )/(ΔTmMAX ΔTmMIN ),
      (Eq. 6)


      where the changes in melting temperatures upon point mutation ΔTmobs, ΔTmMAX, and ΔTmMIN were averages of the apo-monomer data in Refs.
      • Stathopulos P.B.
      • Rumfeldt J.A.
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      ,
      • Furukawa Y.
      • O'Halloran T.V.
      .

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